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Sefik Ilkin Serengil 2024-08-17 08:10:49 +01:00
parent 39a6d24163
commit 52d6873253
1 changed files with 8 additions and 9 deletions
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deepface/modules/verification.py
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@ -115,22 +115,21 @@ def verify(
} }
def extract_embeddings_and_facial_areas( def extract_embeddings_and_facial_areas(
img_path: Union[str, np.ndarray, List[float]], img_path: Union[str, np.ndarray, List[float]], index: int
index: int ) -> Tuple[List[List[float]], List[dict]]:
) -> Tuple[List[List[float]], List[dict]]:
""" """
Extracts facial embeddings and corresponding facial areas from an Extracts facial embeddings and corresponding facial areas from an
image or returns pre-calculated embeddings. image or returns pre-calculated embeddings.
Depending on the type of img_path, the function either extracts Depending on the type of img_path, the function either extracts
facial embeddings from the provided image facial embeddings from the provided image
(via a path or NumPy array) or verifies that the input is a list of (via a path or NumPy array) or verifies that the input is a list of
pre-calculated embeddings and validates them. pre-calculated embeddings and validates them.
Args: Args:
img_path (Union[str, np.ndarray, List[float]]): img_path (Union[str, np.ndarray, List[float]]):
- A string representing the file path to an image, - A string representing the file path to an image,
- A NumPy array containing the image data, - A NumPy array containing the image data,
- Or a list of pre-calculated embedding values (of type `float`). - Or a list of pre-calculated embedding values (of type `float`).
index (int): An index value used in error messages and logging index (int): An index value used in error messages and logging
to identify the number of the image. to identify the number of the image.
@ -150,7 +149,7 @@ def verify(
if silent is False: if silent is False:
logger.warn( logger.warn(
"You passed 1st image as pre-calculated embeddings." f"You passed {index}-th image as pre-calculated embeddings."
"Please ensure that embeddings have been calculated" "Please ensure that embeddings have been calculated"
f" for the {model_name} model." f" for the {model_name} model."
) )
@ -158,7 +157,7 @@ def verify(
if len(img_path) != dims: if len(img_path) != dims:
raise ValueError( raise ValueError(
f"embeddings of {model_name} should have {dims} dimensions," f"embeddings of {model_name} should have {dims} dimensions,"
f" but it has {len(img_path)} dimensions input" f" but {index}-th image has {len(img_path)} dimensions input"
) )
img_embeddings = [img_path] img_embeddings = [img_path]